The invention relates to a system and method of eliminating systematic noise in a stimulus-response system.
Since the development of modern electronics, most processes involving small signal capture have been performed in the frequency domain. This has been the case because it is simple to create analog circuits (e.g. filters, tank circuits, oscillators) which can be tuned to precisely a single frequency. In the example of a lock-in amplifier or an AM radio tuner, all signals except those within only a very narrow bandwidth of a specified frequency are removed, and only those signals in the desired bandwidth are processed further. This filtering procedure greatly reduces the noise in the system by eliminating noise associated with frequencies other than the desired frequency.
A very different approach, with distinct advantages, involves broadband signal capture in the time domain. This method is used in most conventional oscilloscopes. Because signals are observed in the time domain, analysis of signals arising from nonlinear phenomena is far simpler than with frequency domain characteristics. For example, considering the case of an electrical device with a nonlinear current to voltage characteristic, an AC voltage at a particular frequency will generate not only an AC current at the same frequency, but also currents at many harmonics of the fundamental frequency. Precise device analysis then requires characterization of the amplitude and the phase of each harmonic for different values of the AC voltage amplitude applied. This procedure is difficult and is often mathematically intractable. In time domain analysis, one simply observes the current through the device in response to either a sudden voltage step or a voltage pulse. In general, this observation is made with a digital oscilloscope or signal analyzer.
High speed oscilloscopes and other data acquisition schemes are now evolving to the point that they are or will be capable of averaging repetitive signals at a very high rate of speed. There are two basic types of high speed oscilloscopes. One can capture entire waveforms after a single trigger (one-shot oscilloscopes), and the other creates a waveform from a repetitive signal by sampling the signal at varying time intervals after each trigger (sampling oscilloscope).
In general, following a trigger event, the data acquisition system generates some spurious signal which repeats at each trigger. This noise is known as "synchronous" noise because it occurs systematically with each trigger, and it is synchronous to the trigger event. The synchronous noise may arise as a response of the data acquisition to the trigger, as the triggering process itself will create a transient in the system. Additionally, the data acquisition system may generate the noise due to the means used to capture the data. For instance, many systems interleave digital records from several analog to digital converters in order to record data at a high rate of speed. Unavoidably, there is noise generated in switching among the different converters. This "cyclic" noise arises as the system cycles through a sequence of analog to digital converters. Synchronous and cyclic noise may therefore arise in many different data acquisition systems for a wide variety of reasons. The term "systematic noise" is used hereinafter to refer in general to either synchronous noise or cyclic noise.
Breakthroughs in data acquisition technology now allow for measurement of extremely fast signals and also permit unprecedentedly rapid acquisition and signal averaging of repetitive signals. Many commercial single-shot oscilloscopes can average 100 waveforms consisting of 1000 points each in one second. Some data acquisition systems, built for high speed signal averaging, can average around 500,000 waveforms consisting of 1000 points each second. These systems have very little "dead-time" between triggers, and they are capable of rapidly adding waveforms in the form of long arrays of numerical data. This is frequently done with some type of hard-wired array or parallel processing. These high speed signal averaging systems lose only a small fraction of the data to digital signal processing delays. In principle, they can be as efficient as analog systems for signal capture.
Synchronous or cyclic noise is a major roadblock to the use of conventional data acquisition systems for small signal capture. While signal averaging in analog systems allows the capture of minute signals from conditions of large noise, synchronous and cyclic noise have placed severe limits on the usable dynamic range of digital data acquisition systems. Some digital systems allow 12 bit dynamic range, with synchronous noise appearing at the level of the least significant bit. This limits the dynamic range of the system to three orders of magnitude. For an acquisition system with a broadband input, many signals fall below the threshold of observability. The desired signal is buried in a deluge of synchronous noise. This poor dynamic range contrasts with narrow band analog systems which, using appropriate filtering, can extract minuscule signals from very noise backgrounds.
Accordingly, it is an object of the present invention to provide a system and method which accommodates enormous reduction of both synchronous and cyclic noise in systems used for measuring repetitive signals, which are, in general, signals that are the response to a stimulus.
It is a further object of the present invention to provide a system and method which allows for both the extraction of very small signals in conditions of poor signal to noise, and permits retention of high fidelity of signals, despite synchronous noise, for conditions of higher signal to noise ratios.